Breast cancer is the most commonly diagnosed form of cancer in women and the second-leading cause of cancer-related death behind lung cancer. In Canada in 2004, there were 21200 newly diagnosed cases of breast cancer and 5200 deaths from breast cancer. In the same year, there were 9800 cases of lung cancer and 8200 deaths from lung cancer.
Breast cancer increases in prevalence with age: among newly diagnosed patients, 21% are younger than 50, 49% are between 50 and 69, and 30% are 70 or older. Because of the increased risk of developing breast cancer with age, Health Canada has recommended that women over 50 receive a screening mammogram every two years; other western countries have similar screening policies in place. X-ray mammography is the primary method for early detection of breast cancer and is capable of detecting signs of cancer too subtle or small to be detected by either self-examination or routine physical examination by a physician.
X-ray mammography consists of an x-ray of the breast tissue under transverse compression. Suspicious abnormalities include clusters of microcalcifications, masses or deformations. Microcalcifications are clusters of calcium compound deposits left by several biological processes; most notably for cancer screening, they are sometimes, though not always, secreted by rapidly dividing cells such as cancer cells. Microcalcifications alone show a high correlation with breast cancer, but their appearance alone does not guarantee the presence of cancer, nor does their absence negate the possibility of cancer. Because of this uncertainty, any current automated methods which use only the presence of microcalcifications to mark suspicious images are necessarily limited in their capacity to correctly identify all images showing abnormalities.
Interpretation of mammograms is a difficult process for several reasons. Because the images are formed from x-rays passing through the tissue, contrast in the image depends on differences in the absorption rates of different materials within the tissue; however, these differences are much more subtle between the types of soft tissues in the breast than they are between bone and soft tissue in a chest x-ray, for example. The indications of cancer in an image are often also very subtle, such as small distortions in the structure of the ductile tissue of the breast or the presence of small clusters of microcalcifications.
FIG. 1 shows two typical mammography images: the left image shows a healthy patient, while the right image shows a cancerous mass. These images are medial-lateral images as signified by the ML marker on the x-ray film (the ML is reversed since the image is reflected), and are taken with the x-rays passing horizontally through the tissue while the breast is compressed between two vertical plates. The other common image view is cranial-caudal, typically denoted as CC, which is taken with x-rays passing vertically through the tissue while the breast is compressed between two horizontal plates. Breast tissue can vary greatly in appearance between patients depending on the relative amounts of glandular and fatty tissue present, which appear as relatively bright and dim regions, respectively, further adding to the challenge of detecting abnormalities within a particular patient's image.
A major challenge in the interpretation of mammograms is the small percentage of images that show abnormalities. One typical clinic diagnosed 6.4 cancers per 1000 patients; at two medial-lateral images per patient, this means only one in 300 images showed signs of cancer. This low rate of incidence potentially decreases specificity; a larger number of normal images that are classified as abnormal. Since positive findings require a patient to undergo further procedures this adds cost to the system and creates potentially unfounded anxiety in the patient. For example, in the above study 5-7% of women were recalled for further tests, though only one in ten of those recalled were actually positive for cancer.
Typical computer aided detection (CAD) systems deal with the subtlety of cancer signs on images by marking all suspicious regions in images for radiologists to re-examine. This approach may increase the number of cancer cases which are correctly diagnosed, but it also increases the number of images that a radiologist must study in greater detail and may increase the number of healthy patients recalled as being suspect for cancer. The performance of these systems is no better than that of a general radiologist reading a film.